Cloudinary Blog

API for extracting semantic image data - colors, faces, Exif data and more

When images are involved, web developers have a large set of relevant tools at their disposal. You can display images in your web sites and mobile applications. You can manipulate and transform such images using image editing and manipulation software or cloud-based solutions like Cloudinary. But there are other types of data embedded in image files that can add unique semantic information to the images and are hardly ever used.
 
Consider what new designs can appear if your graphics designer could assume that only blue themed user uploaded photos will be featured on your homepage. What about featuring only photos that show your users' faces? How about photos taken with new DSLR model cameras rather than older pocket ones? Only photos taken in the GPS vicinity of your website visitor? We believe that such capabilities can offer a new, important tool for web design and development. 
 
Unfortunately, such semantic data is usually locked safely within the images and rarely utilized by developers and designers. We hope that we can change that by introducing a new Cloudinary API that allows you to easily extract rich information regarding your website and mobile application's photos. Using this information you can search, sort and classify your images in amazing new ways.
 

Predominant Colors & Color Histogram

Image search services such as Google Image Search allow you to filter your image search to show only images of a certain color. How is it done? Each image is analyzed and the colors of the images are mapped to one or more leading colors.
 
Cloudinary now supports finding the leading colors of a given image using a standard palette of 12 main colors. Since Cloudinary is a cloud-based service, all image processing is done online and no software installation is required on your side.
 
Finding the predominant colors in an image is also useful for stock-photo sites that wants to allow you to narrow photo searching by colors (see our previous post of how-to quickly build a stock-photo site with Cloudinary) and for e-commerce sites. For example: if you have a fashion site, and you want your users to browse only blue or red shirts.
 
For example, the following image with the public ID 'fashion1' was uploaded to Cloudinary:
 
 
 
Using Cloudinary's Admin API, you can extract the photo's main colors by setting the 'colors' parameter to true (see reference documentation). Here are examples for Ruby, PHP, Node.js and Python:
Cloudinary::Api.resource('fashion1', :colors => true)
$api->resource("fashion1", array("colors" => TRUE));
cloudinary.api.resource('fashion1',  
                        function(result)  { console.log(result) }, { colors: true });
cloudinary.api.resource("fashion1", colors = True)
 
Below is the JSON result of this API call. It seems that the main colors of this image are white (50.7%) and blue (27.8%), with touches of gray and brown. Cool.
{
  "public_id": "fashion1",
  "width": 225,
  "height": 380,
  ...
  "predominant": {
    "google": [
      [ "white", 50.7 ],
      [ "blue",  27.8 ],
      [ "gray", 11.2 ],
      [ "brown", 5.1]
    ]
  }
}
Using this info, you can keep the color mapping in your model and allow clothes to be searched based on colors. Searching for blue clothes should return this product.
 
Another result you get as part of the color information API is a histogram of 32 RGB colors that best represent the image. The following JSON snippet was also included in the result of the API call.
{
  "public_id": "fashion1",
  ...
  "colors": [["#FFFFFF", 50.7], ["#011B43", 5.8], ["#5077A7", 4.9], ["#031235", 4.3], ["#F4CBB4", 3.3], ["#3A6498", 1.9], ["#6284AF", 1.9], ["#2D5E95", 1.9], ["#30578B", 1.8], ["#080918", 1.8], ["#E5B09D", 1.8], ["#36262F", 1.7], ["#264876", 1.6], ["#281A25", 1.5], ["#486A99", 1.4], ["#E3D6CF", 1.4], ["#4D3135", 1.4], ["#07264F", 1.2], ["#664E55", 1.1], ["#6E443C", 1.0]]
}
As you can see, you get RGB format and percentage breakdown of the 32 colors that best represent the image. '#FFFFFF' is white, representing around half of the image, followed by multiple blue shades (e.g., '#011B43' is 5.8%).
 

Face detection info 

Cloudinary supports face detection based cropping and pixelation. Either a single face or multiple faces can be automatically detected. Our API now supports returning additional information regarding the detected faces in an uploaded photo. 
 
Simply set the 'faces' parameter to true in the same method we showed above for 'colors'. Note that you can enable multiple flags in a single call for fetching all information at once. The result includes the exact coordinates of all detected faces, allowing you to easily find out how many faces are available in the photo and their exact positions.
 
The following Ruby command asks for the faces information of the 'fashion1' image:
Cloudinary::Api.resource('fashion1', :faces => true)
Here is the JSON result:
{
  "public_id": "fashion1",
  ...
  "faces": [[99, 21, 64, 87]]
}
 
As you can see, a single face was correctly detected. It is positioned in the 99,21 - 64,87 rectangle of the original image.
 
Same works for images with multiple faces:
 
{
  ...
  "faces":  [ [513, 19, 38, 52], [409, 26, 40, 54], [79, 31, 43, 59], [232, 32, 40, 54], [321, 33, 41, 57], [160, 37, 43, 59], [211, 153, 43, 59], [503, 151, 43, 59], [113, 162, 40, 54], [427, 160, 45, 61], [307, 172, 48, 65] ]
}
Note that face detection does not achieve 100% accuracy. If you need better accuracy, human moderation is recommended.
 

Camera information - Exchangeable image file format (Exif)

**Update March 2017: The exif parameter has been deprecated. The exif data can now be extracted using the image_metadata parameter.
 
Modern digital cameras and smartphones store additional metadata as part of the image files you shoot. Such information includes picture orientation, timestamps, camera model information, photo exposure, GPS location and more.
 
By setting the 'exif' parameter to true, Cloudinary's API can return the image's metadata (see our reference documentation). In the sections above we've shown how to use the Admin API for fetching information of previously uploaded images. You can also request this information while uploading the photos, so it is returned as part of an upload response.
 
For example, the following PHP command uploaded to Cloudinary a photo that was taken by an iPhone 4 in a portrait orientation.
\Cloudinary\Uploader::upload("exif_sample.jpeg", 
   array("public_id" => "exif_sample", "colors" => TRUE, "exif" => TRUE))
 
Here is the JSON of the upload response including the requested Exif and Colors information:
{ 
  "public_id": "exif_sample",
  "width": 2592,
  "height": 1936,
  ...
  "exif": {
    "ApertureValue": "4281/1441",
    "ColorSpace": "1",
    "ComponentsConfiguration": "1, 2, 3, 0",
    "Compression": "6",
    "DateTime": "2010:12:27 11:17:34",
    "DateTimeDigitized": "2010:12:27 11:17:34",
    "DateTimeOriginal": "2010:12:27 11:17:34",
    "ExifImageLength": "1936",
    "ExifImageWidth": "2592",
    "ExifOffset": "204",
    "ExifVersion": "48, 50, 50, 49",
    "ExposureMode": "0",
    "ExposureProgram": "2",
    "ExposureTime": "1/4309",
    "Flash": "24",
    "FlashPixVersion": "48, 49, 48, 48",
    "FNumber": "14/5",
    "FocalLength": "77/20",
    "GPSAltitude": "20723/924",
    "GPSAltitudeRef": "0",
    "GPSImgDirection": "42155/344",
    "GPSImgDirectionRef": "T",
    "GPSInfo": "574",
    "GPSLatitude": "21/1, 768/100, 0/1",
    "GPSLatitudeRef": "N",
    "GPSLongitude": "86/1, 4500/100, 0/1",
    "GPSLongitudeRef": "W",
    "GPSTimeStamp": "17/1, 17/1, 3326/100",
    "ISOSpeedRatings": "80",
    "JPEGInterchangeFormat": "870",
    "JPEGInterchangeFormatLength": "9932",
    "Make": "Apple",
    "MeteringMode": "1",
    "Model": "iPhone 4",
    "Orientation": "6",
    "ResolutionUnit": "2",
    "SceneCaptureType": "0",
    "SensingMethod": "2",
    "Sharpness": "2",
    "ShutterSpeedValue": "4781/396",
    "Software": "4.2.1",
    "SubjectArea": "1295, 967, 699, 696",
    "WhiteBalance": "0",
    "XResolution": "72/1",
    "YCbCrPositioning": "1",
    "YResolution": "72/1"
  },
  "colors":[["#CBC9C5",10.2],["#C4BCB4",9.0],["#1888AB",6.0],["#202618",6.0],["#226391",5.4],["#223A62",4.3],["#B9B4AD",3.8],["#2F88A1",3.5],["#C9C3BA",3.4],["#7492B2",3.4],["#157193",3.1],["#96ABCC",2.9],["#C8B495",2.8],["#4F97AB",2.8],["#484033",2.7],["#669FAD",2.5],["#A0A29E",2.4],["#38A7C8",2.3],["#57A5B7",2.3],["#2D8FAF",2.2],["#ACCADC",2.1],["#073554",2.0],["#60AFC7",2.0],["#1D4A6F",2.0],["#A39477",1.9],["#D1C4A0",1.8],["#296F96",1.7],["#4F6E91",1.5],["#5F5F57",1.4],["#90AECB",1.0]],
  "predominant": {"google":[["teal",41.7],["brown",35.6],["blue",12.1],["green",8.4]]
}
By the way, you can also use Cloudinary's Exif-based automatic rotation by setting the 'angle' parameter ('a' for URLs) to 'exif'. For example:
 
 
 

Summary

With the additional knowledge of image metadata and semantic information, you can enhance your image rich web and mobile applications with little effort, while Cloudinary does all the heavy lifting for you. These additional layers of information adds an important aspect that allows Cloudinary to offer a better than ever cloud-based solution to all your online image management and manipulation needs. 
 
All these new features were requested by Cloudinary's users and we thank all of you for that. We have plenty more ideas for enhancing Cloudinary's capabilities in this area and would love to hear your feedback and suggestions.
 
The ability to fetch Exif, FacesPredominant colors and Color histogram is now available to all of Cloudinary's plans, free and paid. Click here to setup a free Cloudinary account.

Recent Blog Posts

Embed Images in Email Campaigns at Scale

By Sourav Kundu
Embed Images in Email Campaigns at Scale

We live in an era of information overload and attention is the real currency. Marketers are constantly looking for new ways to reach you, to advertise products and services that they think could improve your lives.

Read more
Build the Back-End For Your Own Instagram-style App with Cloudinary

Github Repo

Managing media files (processing, storage and manipulation) is one of the biggest challenges we encounter as practical developers. These challenges include:

A great service called Cloudinary can help us overcome many of these challenges. Together with Cloudinary, let's work on solutions to these challenges and hopefully have a simpler mental model towards media management.

Read more

Build A Miniflix in 10 Minutes

By Prosper Otemuyiwa
Build A Miniflix in 10 Minutes

Developers are constantly faced with challenges of building complex products every single day. And there are constraints on the time needed to build out the features of these products.

Engineering and Product managers want to beat deadlines for projects daily. CEOs want to roll out new products as fast as possible. Entrepreneurs need their MVPs like yesterday. With this in mind, what should developers do?

Read more

Your Web Image is Unnecessarily Bloated

By Christian Nwamba
Your Web Image is Unnecessarily Bloated

As a developer, it seems inefficient to serve a 2000kb JPEG image when we could compress images to optimize the performance without degrading the visual quality.

We are not new to this kind of responsibility. But our productivity will end up being questioned if we do not deliver fast. In order to do so, the community has devised several patterns to help improve productivity. Let's review few of these patterns based on their categories:

Read more

Google For Nigeria: We saw it all…

By Christian Nwamba
Google For Nigeria: We saw it all…

Note from Cloudinary: Christian Nwamba, a frequent Cloudinary contributor, recently attended, and was a main speaker, at the Google Developer Group (GDG) Conference in Lagos, Nigeria. Christian led a session teaching more than 500 developers how to “Build Offline Apps for the Next Billion Users.” The stack he used included JS (Vue), Firebase, Service Workers and Cloudinary. Below is his account of the conference and his talk.

Read more
Viral Images: Securing Images and Video uploads to your systems

When was the last time you got paid $40,000 for a few days of work? That is what happened last year to Russian independent security researcher Andrey Leonov, who discovered that if you upload a specially constructed image file to Facebook, you can make Facebook's internal servers, nested deep within their firewalls, run arbitrary commands to expose sensitive internal files in a way that could easily lead to a data breach.

Read more